BIM education in higher learning institutions: a scientometric review and the Malaysia perspective

Over the last decade, digital applications and Building Information Modelling (BIM) have been introduced in the construction industry to realize a smart construction ecosystem. However, the construction industry has not completely accepted BIM as a standard, and the concept of using BIM applications in universities has not been thoroughly researched. This paper addresses the first scientometric study of BIM education in universities, identifying the state of BIM education practices, skillsets, and the level of BIM education in universities. The paper used scientometric analysis and the VOSviewer mapping technique to assess the most impactful publication sources with the most important impact on BIM education by searching “BIM Education” and using 250 bibliographic data extracted from the Scopus database from 2011-2020 to identify the existing research gaps and research direction. Second, a structured questionnaire was distributed to 343 Year 2 and Year 3 students from two public and two private Malaysian universities that use BIM in their learning. Descriptive data analysis using cross-tabulation in SPSS and relative importance index (RII) were used to analyze the data. The paper revealed two stages of BIM education research; and identified research gaps in the fields of BIM education, architectural education, e-learning, curriculum and information management. The paper also revealed Revit, Cost X and the Glodon Cubicost software as the most used applications, while the common skillsets are design authoring, modelling, and cost estimation. However, both public and private university students mainly design 3D models at BIM Stage 1. The study recommends that institutions and other stakeholders provide continuous BIM training, purchase BIM software, and integrate BIM into the curriculum of Built Environment higher learning institutions for the next generation to be the generation that uses virtual collaborative platforms